Merge branch 'main' of github.com:apache/arrow-datafusion into array-…

…coercion

datafusion/functions-aggregate-common/src/tdigest.rs

@@ -644,7 +644,9 @@ impl TDigest {
         let max = cast_scalar_f64!(&state[3]);
         let min = cast_scalar_f64!(&state[4]);
 
-        assert!(max.total_cmp(&min).is_ge());
+        if min.is_finite() && max.is_finite() {
+            assert!(max.total_cmp(&min).is_ge());
+        }
 
         Self {
             max_size,

datafusion/sqllogictest/test_files/aggregate.slt

@@ -1385,6 +1385,24 @@ NaN
 statement ok
 DROP TABLE tmp_percentile_cont;
 
+# Test for issue where approx_percentile_cont_with_weight
+
+statement ok
+CREATE TABLE t1(v1 BOOL);
+
+statement ok
+INSERT INTO t1 VALUES (TRUE);
+
+# ISSUE: https://github.com/apache/datafusion/issues/12716
+# This test verifies that approx_percentile_cont_with_weight does not panic when given 'NaN' and returns 'inf'
+query R
+SELECT approx_percentile_cont_with_weight('NaN'::DOUBLE, 0, 0) FROM t1 WHERE t1.v1;
+----
+Infinity
+
+statement ok
+DROP TABLE t1;
+
 # csv_query_cube_avg
 query TIR
 SELECT c1, c2, AVG(c3) FROM aggregate_test_100 GROUP BY CUBE (c1, c2) ORDER BY c1, c2

datafusion/wasmtest/Cargo.toml

@@ -60,4 +60,5 @@ wasm-bindgen = "0.2.87"
 wasm-bindgen-futures = "0.4.40"
 
 [dev-dependencies]
-wasm-bindgen-test = "0.3"
+tokio = { workspace = true }
+wasm-bindgen-test = "0.3.44"

datafusion/wasmtest/src/lib.rs

@@ -87,13 +87,14 @@ mod test {
 
     wasm_bindgen_test::wasm_bindgen_test_configure!(run_in_browser);
 
-    #[wasm_bindgen_test]
+    #[cfg_attr(target_arch = "wasm32", wasm_bindgen_test)]
+    #[cfg_attr(not(target_arch = "wasm32"), allow(dead_code))]
     fn datafusion_test() {
         basic_exprs();
         basic_parse();
     }
 
-    #[wasm_bindgen_test]
+    #[wasm_bindgen_test(unsupported = tokio::test)]
     async fn basic_execute() {
         let sql = "SELECT 2 + 2;";
 

dev/update_function_docs.sh

@@ -58,7 +58,11 @@ dev/update_function_docs.sh file for updating surrounding text.
 
 # Aggregate Functions (NEW)
 
-This page is a WIP and will replace the Aggregate Functions page once completed.
+Note: this documentation is in the process of being migrated to be  [automatically created from the codebase].
+Please see the [Aggregate Functions (old)](aggregate_functions.md) page for
+the rest of the documentation.
+
+[automatically created from the codebase]: https://github.com/apache/datafusion/issues/12740
 
 Aggregate functions operate on a set of values to compute a single result.
 EOF
@@ -105,7 +109,12 @@ dev/update_function_docs.sh file for updating surrounding text.
 
 # Scalar Functions (NEW)
 
-This page is a WIP and will replace the Scalar Functions page once completed.
+Note: this documentation is in the process of being migrated to be [automatically created from the codebase].
+Please see the [Scalar Functions (old)](aggregate_functions.md) page for
+the rest of the documentation.
+
+[automatically created from the codebase]: https://github.com/apache/datafusion/issues/12740
+
 EOF
 
 echo "Running CLI and inserting scalar function docs table"
@@ -151,9 +160,16 @@ dev/update_function_docs.sh file for updating surrounding text.
 
 # Window Functions (NEW)
 
-This page is a WIP and will replace the Window Functions page once completed.
+Note: this documentation is in the process of being migrated to be  [automatically created from the codebase].
+Please see the [Window Functions (Old)](window_functions.md) page for
+the rest of the documentation.
+
+[automatically created from the codebase]: https://github.com/apache/datafusion/issues/12740
 
-A _window function_ performs a calculation across a set of table rows that are somehow related to the current row. This is comparable to the type of calculation that can be done with an aggregate function. However, window functions do not cause rows to become grouped into a single output row like non-window aggregate calls would. Instead, the rows retain their separate identities. Behind the scenes, the window function is able to access more than just the current row of the query result
+A _window function_ performs a calculation across a set of table rows that are somehow related to the current row.
+This is comparable to the type of calculation that can be done with an aggregate function.
+However, window functions do not cause rows to become grouped into a single output row like non-window aggregate calls would.
+Instead, the rows retain their separate identities. Behind the scenes, the window function is able to access more than just the current row of the query result
 
 Here is an example that shows how to compare each employee's salary with the average salary in his or her department:
 

docs/source/user-guide/sql/aggregate_functions.md

@@ -21,6 +21,12 @@
 
 Aggregate functions operate on a set of values to compute a single result.
 
+Note: this documentation is in the process of being migrated to be [automatically created from the codebase].
+Please see the [Aggregate Functions (new)](aggregate_functions_new.md) page for
+the rest of the documentation.
+
+[automatically created from the codebase]: https://github.com/apache/datafusion/issues/12740
+
 ## General
 
 - [avg](#avg)

docs/source/user-guide/sql/aggregate_functions_new.md

@@ -27,7 +27,11 @@ dev/update_function_docs.sh file for updating surrounding text.
 
 # Aggregate Functions (NEW)
 
-This page is a WIP and will replace the Aggregate Functions page once completed.
+Note: this documentation is in the process of being migrated to be [automatically created from the codebase].
+Please see the [Aggregate Functions (old)](aggregate_functions.md) page for
+the rest of the documentation.
+
+[automatically created from the codebase]: https://github.com/apache/datafusion/issues/12740
 
 Aggregate functions operate on a set of values to compute a single result.
 

docs/source/user-guide/sql/scalar_functions.md

@@ -19,6 +19,14 @@
 
 # Scalar Functions
 
+Scalar functions operate on a single row at a time and return a single value.
+
+Note: this documentation is in the process of being migrated to be [automatically created from the codebase].
+Please see the [Scalar Functions (new)](scalar_functions_new.md) page for
+the rest of the documentation.
+
+[automatically created from the codebase]: https://github.com/apache/datafusion/issues/12740
+
 ## Math Functions
 
 - [abs](#abs)

docs/source/user-guide/sql/scalar_functions_new.md

@@ -27,7 +27,11 @@ dev/update_function_docs.sh file for updating surrounding text.
 
 # Scalar Functions (NEW)
 
-This page is a WIP and will replace the Scalar Functions page once completed.
+Note: this documentation is in the process of being migrated to be [automatically created from the codebase].
+Please see the [Scalar Functions (old)](aggregate_functions.md) page for
+the rest of the documentation.
+
+[automatically created from the codebase]: https://github.com/apache/datafusion/issues/12740
 
 ## Math Functions
 

docs/source/user-guide/sql/window_functions.md

@@ -19,7 +19,15 @@
 
 # Window Functions
 
-A _window function_ performs a calculation across a set of table rows that are somehow related to the current row. This is comparable to the type of calculation that can be done with an aggregate function. However, window functions do not cause rows to become grouped into a single output row like non-window aggregate calls would. Instead, the rows retain their separate identities. Behind the scenes, the window function is able to access more than just the current row of the query result
+A _window function_ performs a calculation across a set of table rows that are somehow related to the current row.
+
+Note: this documentation is in the process of being migrated to be [automatically created from the codebase].
+Please see the [Window Functions (new)](window_functions_new.md) page for
+the rest of the documentation.
+
+[automatically created from the codebase]: https://github.com/apache/datafusion/issues/12740
+
+Window functions are comparable to the type of calculation that can be done with an aggregate function. However, window functions do not cause rows to become grouped into a single output row like non-window aggregate calls would. Instead, the rows retain their separate identities. Behind the scenes, the window function is able to access more than just the current row of the query result
 
 Here is an example that shows how to compare each employee's salary with the average salary in his or her department:
 

docs/source/user-guide/sql/window_functions_new.md

@@ -27,9 +27,16 @@ dev/update_function_docs.sh file for updating surrounding text.
 
 # Window Functions (NEW)
 
-This page is a WIP and will replace the Window Functions page once completed.
+Note: this documentation is in the process of being migrated to be [automatically created from the codebase].
+Please see the [Window Functions (Old)](window_functions.md) page for
+the rest of the documentation.
 
-A _window function_ performs a calculation across a set of table rows that are somehow related to the current row. This is comparable to the type of calculation that can be done with an aggregate function. However, window functions do not cause rows to become grouped into a single output row like non-window aggregate calls would. Instead, the rows retain their separate identities. Behind the scenes, the window function is able to access more than just the current row of the query result
+[automatically created from the codebase]: https://github.com/apache/datafusion/issues/12740
+
+A _window function_ performs a calculation across a set of table rows that are somehow related to the current row.
+This is comparable to the type of calculation that can be done with an aggregate function.
+However, window functions do not cause rows to become grouped into a single output row like non-window aggregate calls would.
+Instead, the rows retain their separate identities. Behind the scenes, the window function is able to access more than just the current row of the query result
 
 Here is an example that shows how to compare each employee's salary with the average salary in his or her department: